Online allocation algorithm of digital story course resources based on deep learning

Ke Xu, Julina Ismail Kamal
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Abstract

The online allocation of course resources is a part of the field of cloud computing. Studying the allocation of digital story course resources through cloud computing architecture can not only meet the requirements of cloud computing resource allocation, but also improve the utilization efficiency of digital story course resources. This paper mainly proposes an application-oriented resource allocation algorithm based on deep learning. This online allocation algorithm mainly quantifies the characteristics of the data, and more accurately creates the server resources required by the digital story course. In addition, the workload prediction model is integrated into the online allocation algorithm, which can Ensure that curriculum resources and teaching are more matched, so as to give full play to the value of resource use.
基于深度学习的数字故事课程资源在线分配算法
课程资源的在线分配是云计算领域的一部分。通过云计算架构研究数字故事课程资源的配置,不仅可以满足云计算资源配置的要求,而且可以提高数字故事课程资源的利用效率。本文主要提出了一种基于深度学习的面向应用的资源分配算法。该在线分配算法主要量化了数据的特征,更准确地创建了数字故事课程所需的服务器资源。此外,将工作量预测模型集成到在线分配算法中,可以保证课程资源与教学更加匹配,从而充分发挥资源的使用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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